Early cancer detection currently relies on screening the entire at-risk population, such as with colonoscopy and mammography. Thus, frequent and invasive surveillance of patients at risk for developing cancer carries financial, physical, and emotional burdens because clinicians lack tools to accurately predict which patients will actually progress into malignancy.
Cancer develops through a series of genetic and epigenetic events that result in architectural changes in the cell nucleus. As such, alteration in nuclear architecture has been the gold standard in pathology for cancer diagnosis and prognosis. Given that nuclear architecture is conventionally assessed at the two-dimensional (2D) microscopic images (e.g., approximately 500 nm resolution) of tissue sections stained with hemotoxylin and eosin, the characteristic morphological changes identified in cancerous or precancerous cells are limited to mostly micron-scale features, and are considered to be a late manifestation of carcinogenesis. These features include increased nuclear size, irregular nuclear shape, and coarse chromatin texture. Many structural abnormalities observable at the micro-scale do not occur until an advanced stage, making it difficult to distinguish early-stage cancers from benign conditions.
Further, the detection of pre-cancer or early-stage cancer is not sufficient in many clinical settings. As many pre-cancers or early-stage cancers will never progress into invasive cancer, detection may lead to unnecessary treatment in the absence of aggressive cancer. This unnecessary treatment may do more harm than good to the patient at a high cost. Therefore, it is important to not only identify pre-cancer or early-stage cancer, but also predict which pre-cancer or early-stage cancer is likely to develop into a more invasive form (e.g., prognosis). This microscale nuclear morphology has some prognostic value, but its accuracy is somewhat limited. For higher accuracy and sensitivity in cancer diagnosis and prognosis, there is an urgent need for new methods and systems to assess nuclear architectural changes at the nanoscale, well beyond micron-scale features, with a high throughput that is clinically applicable.
Due to the advancement in understanding cancer genome and epigenome, it is now recognized that the genome function is not just regulated by the linear sequence of DNA, and the spatial organization of chromatin plays a key role in cancer development. The detection of whole-genome level 3D spatial distribution of chromatin at a single cell nucleus level in clinically prepared samples seems to be an astonishing task. On the other hand, the detection of the changes in the 3D spatial arrangement and the chromatin density variation in the cell nucleus as the downstream structural changes of complex genomic and epigenomic changes in carcinogenesis may have potential as a high throughput approach.